International portfolio management with affine policies

While dynamic decision making has traditionally been represented as scenario trees, these may become severely intractable and difficult to compute with an increasing number of time periods. We present an alternative tractable approach to multiperiod international portfolio optimization based on an affine dependence between the decision variables and the past returns. Because local asset and currency returns are modeled separately, the original model is non-linear and non-convex. With the aid of robust optimization techniques, however, we develop a tractable semidefinite programming formulation of our model, where the uncertain returns are contained in an ellipsoidal uncertainty set. We add to our formulation the minimization of the worst case value-at-risk and show the close relationship with robust optimization. Numerical results demonstrate the potential gains from considering a dynamic multiperiod setting relative to a single stage approach.

► We apply linear decision rules to a robust multistage international portfolio.
► The worst case value-at-risk over the entire optimization period is minimized.
► We compare the minimization of the worst case value-at-risk to robust optimization.
► Multistage models yield on average a greater return rate than single stage models.
► Simulations show the robustness of the model for different returns distributions.